Bank of America Corporation
Evaluating Supervised Learning Models Through Comparison of Actual and Predicted Model Outputs

Abstract:

Aspects of the disclosure relate to evaluating supervised learning models. A computing platform may receive initial training data, train supervised learning models using the initial training data, and form a composite model based on the supervised learning models. The computing platform may receive additional training data and corresponding prediction parameters, indicating actual outcomes. The computing platform may input the additional training data into the composite model to generate model-predicted outcome data, and may compare the model-predicted outcome data to the actual outcomes. Based on results of the comparison of the model-predicted outcome data to the actual outcomes, the computing platform may score each of the supervised learning models to reflect corresponding reliability levels. The computing platform may store a matrix relating the scores to their corresponding supervised learning models, which may cause the computing platform to weight results obtained from each supervised learning model when applying the composite model.